---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: data2vec-audio-base-960h-ft
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# data2vec-audio-base-960h-ft

This model is a fine-tuned version of [facebook/data2vec-audio-base-960h](https://huggingface.co/facebook/data2vec-audio-base-960h) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0146
- Accuracy: 0.9967

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Accuracy | Validation Loss |
|:-------------:|:-----:|:-----:|:--------:|:---------------:|
| 0.1427        | 1.0   | 8558  | 0.9941   | 0.0271          |
| 0.0799        | 2.0   | 17116 | 0.9964   | 0.0154          |
| 0.0889        | 3.0   | 25674 | 0.9967   | 0.0146          |
| 0.0843        | 4.0   | 34232 | 0.9967   | 0.0162          |
| 0.0925        | 5.0   | 42790 | 0.9961   | 0.0151          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.11.0+cpu
- Datasets 2.10.1
- Tokenizers 0.12.1